Robust localization and identification of African clawed frogs in digital images
Yükleniyor...
Dosyalar
Tarih
2014-09
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Science BV
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
We study the automatic localization and identification of African clawed frogs (Xenopus laevis sp.) in digital images taken in a laboratory environment. We propose a novel and stable frog body localization and skin pattern window extraction algorithm. We show that it compensates scale and rotation changes very well. Moreover, it is able to localize and extract highly overlapping regions (pattern windows) even in the cases of intense affine transformations, blurring, Gaussian noise, and intensity transformations. The frog skin pattern (i.e. texture) provides a unique feature for the identification of individual frogs. We investigate the suitability of five different feature descriptors (Gabor filters, area granulometry, HoG,(1) dense SIFT,(2) and raw pixel values) to represent frog skin patterns. We compare the robustness of the features based on their identification performance using a nearest neighbor classifier. Our experiments show that among five features that we tested, the best performing feature against rotation, scale, and blurring modifications was the raw pixel feature, whereas the SIFT feature was the best performing one against affine and intensity modifications.
Açıklama
Anahtar Kelimeler
Xenopus laevis, Automated frog identification, Skin pattern recognition, Area granulometry, Sift, HoG, Texture analysis, Classification, Similarity, Retrieval, Features
Kaynak
Ecological Informatics
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
23
Sayı
SI
Künye
Tek, F. B., Cannavo, F., Nunnari, G. & Kale, İ. (2014). Robust localization and identification of african clawed frogs in digital images. Ecological Informatics, 23, 3-12. doi:10.1016/j.ecoinf.2013.09.005
